In an x-ray computed tomography (“CT”) system, an x-ray source projects a fan- or cone-shaped beam of x-rays that is collimated to lie within an x-y plane of a Cartesian coordinate system, termed the “imaging plane.” The x-ray beam passes through the object being imaged, such as a medical patient, and impinges upon an array of radiation detectors. The intensity of the transmitted radiation is dependent upon the attenuation of the x-ray beam by the object, and each detector produces a separate electrical signal that is a measurement of the beam attenuation. The attenuation measurements from all of the detectors are acquired separately to produce a transmission profile at a particular view angle.
The source and detector array in a conventional CT system are rotated on a gantry within the imaging plane, and around the object so that the angle at which the x-ray beam intersects the object constantly changes. A group of x-ray attenuation measurements from the detector array at a given angle is referred to as a “view,” and a “scan” of the object includes a set of views acquired at different angular orientations during one revolution of the x-ray source and detector. In a 2D scan, data is processed to reconstruct an image that corresponds to a two-dimensional slice taken through the object. The prevailing method for reconstructing an image from 2D data is referred to in the art as the filtered backprojection technique. This process converts the attenuation measurements from a scan into integers called “CT numbers,” or “Hounsfield units,” which are used to control the brightness of a corresponding pixel on a display.
CT imaging is well suited to provide clinically useful images related to a variety of medical conditions. For example, CT pulmonary angiography (CTPA) is currently the diagnostic standard for investigating a suspected pulmonary embolism. A pulmonary embolism is a sudden blockage, such as a clot, in a lung artery due to an embolus that is formed in one part of the body and travels through the bloodstream to an artery of the lung. It is a common cardiovascular emergency with about 600,000 cases occurring annually and causing approximately 200,000 deaths in the United States. Most patients who succumb to pulmonary embolism do so within the first few hours following the event.
A major clinical challenge, particularly in an emergency department, is to quickly and correctly diagnose patients with a pulmonary embolism and dispatch them to treatment, so that hazardous yet life-saving therapy can be prescribed appropriately. Unfortunately, pulmonary embolisms are among the most difficult conditions to diagnose because its primary symptoms are protean and may be manifested by a number of other conditions that require different therapeutic interventions. The correct diagnosis of a pulmonary embolism has been found to be overlooked in as many as 84% of cases (which is estimated at about 450,000 cases each year in the United States), resulting in more than 34,000 preventable deaths, assuming a mortality rate of 7.7%. Not surprisingly then, the Surgeon General has called for action to help prevent deep vein thrombosis (DVT) and pulmonary embolisms.
As noted above, computed tomography or CT is used to visualize the pulmonary arteries so that a highly trained medical professional, such as a radiologist, can examine the CT images for indications of a pulmonary embolism. As such, medical imaging plays a key role in conducting clinical evaluations to diagnose pulmonary embolisms. Specifically, CTPA reveals embolus as a dark region residing in bright vessel lumen. As an imaging protocol, each CTPA scan consists of hundreds of axial images. The interpretation of these images is complex and time consuming because of the intricate branching structure of the pulmonary arteries, the demand for specialized knowledge to distinguish a pulmonary embolism from the various causes of cardiopulmonary pathology that may resemble a pulmonary embolism, and a myriad of artifacts that may obscure or mimic emboli (e.g., flow-related artifacts, streak artifacts, lymph nodes, and the like). The accuracy and efficiency of interpreting such large 3-D image datasets is further limited by human factors, such as attention span and eye fatigue.
Unfortunately, incorrect CTPA interpretations are not infrequent in clinical practice. The number of CTPA examinations has increased by an order of magnitude over the past decade, while studies have found that the rate of true positive examinations has fallen to about 5-10%.
There is therefore a need to mitigate rapidly mounting radiologist workloads and improve the efficiency and accuracy of a pulmonary embolism diagnosis. Accordingly, it is desirable to provide methods, systems, and media for generating and analyzing medical images having elongated structures that overcome these and other deficiencies of the prior art. For example, methods, systems, and media are provided that process one or more images by reformatting the image planes to be in alignment with the longitudinal axis of an elongated structure, such as a vessel, so that the user can scroll along the axis, spin around the longitudinal axis, and perform other operations, thereby facilitating a thorough inspection of the elongated structure from multiple perspectives and providing compelling demonstration of any defects (e.g., arterial filling defects).